Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program.

BACKGROUND: We are developing 10 de novo population-level mathematical models in 4 malignancies (multiple myeloma and bladder, gastric, and uterine cancers). Each of these sites has documented disparities in outcome that are believed to be downstream effects of systemic racism. METHODS: Ten models are being independently developed as part of the Cancer Intervention and Surveillance Modeling Network incubator program. These models simulate trends in cancer incidence, early diagnosis, treatment, and mortality for the general population and are stratified by racial subgroup. Model inputs are based on large population datasets, clinical trials, and observational studies. Some core parameters are shared, and other parameters are model specific. All models are microsimulation models that use self-reported race to stratify model inputs. They can simulate the distribution of relevant risk factors (eg, smoking, obesity) and insurance status (for multiple myeloma and uterine cancer) in US birth cohorts and population. DISCUSSION: The models aim to refine approaches in prevention, detection, and management of 4 cancers given uncertainties and constraints. They will help explore whether the observed racial disparities are explainable by inequities, assess the effects of existing and potential cancer prevention and control policies on health equity and disparities, and identify policies that balance efficiency and fairness in decreasing cancer mortality.

Multi-state network meta-analysis of progression and survival data.

Multiple randomized controlled trials, each comparing a subset of competing interventions, can be synthesized by means of a network meta-analysis to estimate relative treatment effects between all interventions in the evidence base. Here we focus on estimating relative treatment effects for time-to-event outcomes. Cancer treatment effectiveness is frequently quantified by analyzing overall survival (OS) and progression-free survival (PFS). We introduce a method for the joint network meta-analysis of PFS and OS that is based on a time-inhomogeneous tri-state (stable, progression, and death) Markov model where time-varying transition rates and relative treatment effects are modeled with parametric survival functions or fractional polynomials. The data needed to run these analyses can be extracted directly from published survival curves. We demonstrate use by applying the methodology to a network of trials for the treatment of non-small-cell lung cancer. The proposed approach allows the joint synthesis of OS and PFS, relaxes the proportional hazards assumption, extends to a network of more than two treatments, and simplifies the parameterization of decision and cost-effectiveness analyses.

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes.

BACKGROUND: There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES: To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS: We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA: We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS: We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.  Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS: We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.  Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.  Combinations of the three most effective QI strategies were estimated to lead to the below effects:  - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;  - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;  - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS: There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.

Bounding the Implications of Noncompliance in Randomized Controlled Trials in Orthopaedics: An Example in Arthroscopic Surgery.

INTRODUCTION: Randomized controlled trials (RCTs) are not impervious to bias especially when there are substantial numbers of patients who cross over from the treatment assigned by randomization to another treatment group, leading to loss of confidence in study results. The goals of this study were to (1) quantify the effects of crossovers on RCTs, (2) describe the specific effects of crossovers on RCTs for arthroscopic meniscectomy for osteoarthritis of the knee (APM/OAK), and (3) assess the confidence in APM/OAK in which there have been substantial numbers of patients crossing over to another treatment group than that assigned. METHODS: Studies were included that were RCTs of APM/OAK with intention-to-treat (ITT) analysis and illustrated the problem of crossovers on confidence in the analysis. Studies were excluded if they consisted of APM for conditions other than OAK or had unavailability of data needed for the analysis. For eligible RCTs, the ITT effect was calculated; bounds for the average treatment effect (ATE) and the complier ATE were assessed by estimating confidence intervals for the bound through robust Bayesian analysis. RESULTS: The eligible studies had different comparators and, therefore, were analyzed individually. Data were not pooled. The most extreme point estimates (with 95% confidence interval) for ITT ranged from -0.01 to 0.04 (-0.16 to 0.16); for ATE with no assumptions, 0.38 (-0.58 to 0.43) to 0.62 (0.56 to 0.70); for ATE with minimum assumptions, -0.50 (-0.22 to 0.10) to 0.61 (0.53 to 0.57); and for complier ATE, -0.01 to 0.07 (-0.22 to 0.24). DISCUSSION: These data suggest large bounds, crossing the threshold of "no effect," which indicates a high degree of uncertainty and low confidence in the RCTs studied. The results demonstrate that when there are crossovers, ITT analyses do not estimate the ATE and confidence in the results of these RCTs is low. DATA AVAILABILITY: All analyzed data are provided in the article. LEVEL OF EVIDENCE: Level I (therapeutic study = RCT).

Semi-automated Tools for Systematic Searches.

Traditionally, literature identification for systematic reviews has relied on a two-step process: first, searching databases to identify potentially relevant citations, and then manually screening those citations. A number of tools have been developed to streamline and semi-automate this process, including tools to generate terms; to visualize and evaluate search queries; to trace citation linkages; to deduplicate, limit, or translate searches across databases; and to prioritize relevant abstracts for screening. Research is ongoing into tools that can unify searching and screening into a single step, and several protype tools have been developed. As this field grows, it is becoming increasingly important to develop and codify methods for evaluating the extent to which these tools fulfill their purpose.

BayCANN: Streamlining Bayesian Calibration With Artificial Neural Network Metamodeling.

Purpose: Bayesian calibration is generally superior to standard direct-search algorithms in that it estimates the full joint posterior distribution of the calibrated parameters. However, there are many barriers to using Bayesian calibration in health decision sciences stemming from the need to program complex models in probabilistic programming languages and the associated computational burden of applying Bayesian calibration. In this paper, we propose to use artificial neural networks (ANN) as one practical solution to these challenges. Methods: Bayesian Calibration using Artificial Neural Networks (BayCANN) involves (1) training an ANN metamodel on a sample of model inputs and outputs, and (2) then calibrating the trained ANN metamodel instead of the full model in a probabilistic programming language to obtain the posterior joint distribution of the calibrated parameters. We illustrate BayCANN using a colorectal cancer natural history model. We conduct a confirmatory simulation analysis by first obtaining parameter estimates from the literature and then using them to generate adenoma prevalence and cancer incidence targets. We compare the performance of BayCANN in recovering these "true" parameter values against performing a Bayesian calibration directly on the simulation model using an incremental mixture importance sampling (IMIS) algorithm. Results: We were able to apply BayCANN using only a dataset of the model inputs and outputs and minor modification of BayCANN's code. In this example, BayCANN was slightly more accurate in recovering the true posterior parameter estimates compared to IMIS. Obtaining the dataset of samples, and running BayCANN took 15 min compared to the IMIS which took 80 min. In applications involving computationally more expensive simulations (e.g., microsimulations), BayCANN may offer higher relative speed gains. Conclusions: BayCANN only uses a dataset of model inputs and outputs to obtain the calibrated joint parameter distributions. Thus, it can be adapted to models of various levels of complexity with minor or no change to its structure. In addition, BayCANN's efficiency can be especially useful in computationally expensive models. To facilitate BayCANN's wider adoption, we provide BayCANN's open-source implementation in R and Stan.

Active learning for efficiently training emulators of computationally expensive mathematical models.

An emulator is a fast-to-evaluate statistical approximation of a detailed mathematical model (simulator). When used in lieu of simulators, emulators can expedite tasks that require many repeated evaluations, such as sensitivity analyses, policy optimization, model calibration, and value-of-information analyses. Emulators are developed using the output of simulators at specific input values (design points). Developing an emulator that closely approximates the simulator can require many design points, which becomes computationally expensive. We describe a self-terminating active learning algorithm to efficiently develop emulators tailored to a specific emulation task, and compare it with algorithms that optimize geometric criteria (random latin hypercube sampling and maximum projection designs) and other active learning algorithms (treed Gaussian Processes that optimize typical active learning criteria). We compared the algorithms' root mean square error (RMSE) and maximum absolute deviation from the simulator (MAX) for seven benchmark functions and in a prostate cancer screening model. In the empirical analyses, in simulators with greatly varying smoothness over the input domain, active learning algorithms resulted in emulators with smaller RMSE and MAX for the same number of design points. In all other cases, all algorithms performed comparably. The proposed algorithm attained satisfactory performance in all analyses, had smaller variability than the treed Gaussian Processes, and, on average, had similar or better performance as the treed Gaussian Processes in six out of seven benchmark functions and in the prostate cancer model.

Pharmacologic and Nonpharmacologic Treatments for Urinary Incontinence in Women: A Systematic Review and Network Meta-analysis of Clinical Outcomes.

Background: Urinary incontinence (UI), a common malady in women, most often is classified as stress, urgency, or mixed. Purpose: To compare the effectiveness of pharmacologic and nonpharmacologic interventions to improve or cure stress, urgency, or mixed UI in nonpregnant women. Data Sources: MEDLINE, Cochrane Central Register of Controlled Trials (Wiley), Cochrane Database of Systematic Reviews (Wiley), EMBASE (Elsevier), CINAHL (EBSCO), and PsycINFO (American Psychological Association) from inception through 10 August 2018. Study Selection: 84 randomized trials that evaluated 14 categories of interventions and reported categorical cure or improvement outcomes. Data Extraction: 1 researcher extracted study characteristics, results, and study-level risk of bias, with verification by another independent researcher. The research team collaborated to assess strength of evidence (SoE) across studies. Data Synthesis: 84 studies reported cure or improvement outcomes (32 in stress UI, 16 in urgency UI, 4 in mixed UI, and 32 in any or unspecified UI type). The most commonly evaluated active intervention types included behavioral therapies, anticholinergics, and neuromodulation. Network meta-analysis showed that all interventions, except hormones and periurethral bulking agents (variable SoE), were more effective than no treatment in achieving at least 1 favorable UI outcome. Among treatments used specifically for stress UI, behavioral therapy was more effective than either α-agonists or hormones in achieving cure or improvement (moderate SoE); α-agonists were more effective than hormones in achieving improvement (moderate SoE); and neuromodulation was more effective than no treatment for cure, improvement, and satisfaction (high SoE). Among treatments used specifically for urgency UI, behavioral therapy was statistically significantly more effective than anticholinergics in achieving cure or improvement (high SoE), both neuromodulation and onabotulinum toxin A (BTX) were more effective than no treatment (high SoE), and BTX may have been more effective than neuromodulation in achieving cure (low SoE). Limitation: Scarce direct (head-to-head trial) evidence and population heterogeneity based on UI type, UI severity, and history of prior treatment. Conclusion: Most nonpharmacologic and pharmacologic interventions are more likely than no treatment to improve UI outcomes. Behavioral therapy, alone or in combination with other interventions, is generally more effective than pharmacologic therapies alone in treating both stress and urgency UI. Primary Funding Source: Patient-Centered Outcomes Research Institute. (PROSPERO: CRD42017069903).

Leveraging Cumulative Network Meta-analysis and Value of Information Analysis to Understand the Evolving Value of Medical Research.

BACKGROUND: Leveraging cumulative network meta-analysis (NMA) and value of information (VOI) analysis, this article aims to understand the evolving value of medical research and to identify gaps in the evidence for future research. METHODS: As an illustration, we identified 31 randomized controlled trials (RCT) from 1980 to 2013 that examined a network of 3 interventions for coronary artery disease: medical therapy (MED), percutaneous coronary intervention (PCI), and coronary artery bypass graft (CABG) surgery. We conducted Bayesian NMA to combine evidence from a new RCT with existing knowledge. Then, using the Duke Databank for Cardiovascular Diseases database, we developed an accelerated failure time model to estimate the joint effects of patient characteristics and treatment choices on survival outcomes. With the estimated coefficients and covariance matrices, we projected survival benefits and its surrounding uncertainty among 50,000 simulated patients treated with MED, PCI, or CABG. The value of resolving residual uncertainty from future trials was quantified through the VOI analysis. We repeated these steps for each published RCT to estimate dynamic changes in VOI estimates. RESULTS: Our cumulative NMA found that CABG conferred a lower, but not statistically significant, mortality than PCI (hazard ratio [HR], 0.90; 95% uncertainty interval, 0.80-1.05). MED had a nonsignificantly higher long-term mortality than PCI (HR, 1.11; 0.98-1.31) but significantly higher than CABG (HR, 1.07; 1.23-1.41). The greatest potential gains from future research would come from additional head-to-head trials between CABG v. PCI with the value of future research equaling 0.27 life years per patient. CONCLUSIONS: The combination of cumulative NMA and VOI approaches can improve the efficiency of comparative effectiveness research by using all of the available evidence to determine future research priorities.

Different evidence summaries have implications for contextualizing findings of meta-analysis of diagnostic tests.

OBJECTIVE: To evaluate diagnostic tests, analysts use meta-analyses to provide inputs to parameters in decision models. Choosing parameter estimands from meta-analyses requires understanding the meta-analytic and decision-making contexts. STUDY DESIGN AND SETTING: We expand on an analysis comparing positron emission tomography (PET), PET with computed tomography (PET/CT), and conventional workup (CW) in women with suspected recurrent breast cancer. We discuss Bayesian meta-analytic summaries (posterior mean over a set of existing studies, posterior estimate in an existing study, posterior predictive mean in a new study) used to estimate diagnostic test parameters (prevalence, sensitivity, specificity) needed to calculate quality-adjusted life years in a decision model contextualizing PET, PET/CT, and CW. RESULTS: The mean and predictive mean give similar estimates, but the latter displays greater uncertainty. Namely, PET/CT outperforms CW on average but may not do better than CW when implemented in future settings. CONCLUSION: Selecting estimands for decision model parameters from meta-analyses requires understanding the relationship between decision settings and meta-analysis studies' settings, specifically whether the former resemble one or all study settings or represents new settings. We provide an algorithm recommending appropriate estimands as input parameters in decision models for diagnostic tests to obtain output parameters consistent with the decision context.

Treatments of Primary Basal Cell Carcinoma of the Skin: A Systematic Review and Network Meta-analysis.

Background: Most interventions for basal cell carcinoma (BCC) have not been compared in head-to-head randomized trials. Purpose: To evaluate the comparative effectiveness and safety of treatments of primary BCC in adults. Data Sources: English-language searches of MEDLINE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Embase from inception to May 2018; reference lists of guidelines and systematic reviews; and a search of ClinicalTrials.gov in August 2016. Study Selection: Comparative studies of treatments currently used in adults with primary BCC. Data Extraction: One investigator extracted data on recurrence, histologic clearance, clinical clearance, cosmetic outcomes, quality of life, and mortality, and a second reviewer verified extractions. Several investigators evaluated risk of bias for each study. Data Synthesis: Forty randomized trials and 5 nonrandomized studies compared 18 interventions in 9 categories. Relative intervention effects and mean outcome frequencies were estimated using frequentist network meta-analyses. Estimated recurrence rates were similar for excision (3.8% [95% CI, 1.5% to 9.5%]), Mohs surgery (3.8% [CI, 0.7% to 18.2%]), curettage and diathermy (6.9% [CI, 0.9% to 36.6%]), and external-beam radiation (3.5% [CI, 0.7% to 16.8%]). Recurrence rates were higher for cryotherapy (22.3% [CI, 10.2% to 42.0%]), curettage and cryotherapy (19.9% [CI, 4.6% to 56.1%]), 5-fluorouracil (18.8% [CI, 10.1% to 32.5%]), imiquimod (14.1% [CI, 5.4% to 32.4%]), and photodynamic therapy using methyl-aminolevulinic acid (18.8% [CI, 10.1% to 32.5%]) or aminolevulinic acid (16.6% [CI, 7.5% to 32.8%]). The proportion of patients reporting good or better cosmetic outcomes was better for photodynamic therapy using methyl-aminolevulinic acid (93.8% [CI, 79.2% to 98.3%]) or aminolevulinic acid (95.8% [CI, 84.2% to 99.0%]) than for excision (77.8% [CI, 44.8% to 93.8%]) or cryotherapy (51.1% [CI, 15.8% to 85.4%]). Data on quality of life and mortality were too sparse for quantitative synthesis. Limitation: Data are sparse, and effect estimates are imprecise and informed by indirect comparisons. Conclusion: Surgical treatments and external-beam radiation have low recurrence rates for the treatment of low-risk BCC, but substantial uncertainty exists about their comparative effectiveness versus other treatments. Gaps remain regarding high-risk BCC subtypes and important outcomes, including costs. Primary Funding Source: Agency for Healthcare Research and Quality. (PROSPERO: CRD42016043353).

Comparative Effectiveness and Safety of Bariatric Procedures in Medicare-Eligible Patients: A Systematic Review.

Importance: The prevalence of obesity in patients older than 65 years is increasing. A substantial number of beneficiaries covered by Medicare meet eligibility criteria for bariatric procedures. Objective: To assess the comparative effectiveness and safety of bariatric procedures in the Medicare-eligible population. Evidence Review: This systematic review was conducted according to the PRISMA guidelines. Articles were identified through searches of PubMed, Embase, CINAHL, PsycINFO, Cochrane Central Trials Registry, Cochrane Database of Systematic Reviews, and scientific information packages from manufacturers, ClinicalTrials.gov, World Health Organization International Clinical Trials Registry Platform, and US Food and Drug Administration drugs and devices portals from January 1, 2000, to June 31, 2017. Randomized and nonrandomized comparative studies that evaluated bariatric procedures in the Medicare-eligible population were eligible. Six researchers extracted data on design, interventions, outcomes, and study quality. Findings were synthesized qualitatively; a planned meta-analysis was not undertaken owing to clinical heterogeneity. Findings: A total of 11 455 citations were screened for eligibility. Of those, 16 met the eligibility criteria. Compared with no surgery or conventional weight-loss treatment, bariatric surgery results in greater weight loss. Overall mortality after 30 days is lower among bariatric patients (hazard ratio, HR, 0.50; 95% CI, 0.31-0.79, in the study with the longest follow-up of 5.9 years), although, based on 1 study, mortality within 30 days of surgery was higher than in nonsurgically treated controls (1.55% vs 0.53%; P < .001). Bariatric surgery is associated with lower risk of cardiovascular disease (HR, 0.59; 95% CI, 0.44-0.79 in the largest study comparison) and with improvements in respiratory, musculoskeletal, metabolic, and renal outcomes (increase in estimated glomerular filtration rate, 9.84; 95% CI, 8.05-11.62 mL/min/1.73m2). Compared with sleeve gastrectomy (SG) and adjustable gastric banding (AGB), Roux-en-Y gastric bypass (RYGB) appears to be associated with greater weight loss (percent excess weight loss, 23.8% [95% CI, 16.2%-31.4%] at the longest follow-up of 4 years) but the 3 procedures have similar associations with most non-weight loss outcomes. Overall postoperative complications are not statistically significantly different between RYGB and SG, although major and/or serious complications are more common after RYGB. However, these associations are susceptible to at least moderate risk of confounding, selection, or measurement biases. Conclusions and Relevance: In the Medicare population, there is low to moderate strength of evidence that bariatric surgery as a weight loss treatment improves non-weight loss outcomes. Well-designed comparative studies are needed to credibly determine the treatment effects for bariatric procedures in this patient population.

Propensity Score-Based Methods in Comparative Effectiveness Research on Coronary Artery Disease.

This review examines the conduct and reporting of observational studies using propensity score-based methods to compare coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), or medical therapy for patients with coronary artery disease. A systematic selection process identified 48 studies: 20 addressing CABG versus PCI; 21 addressing bare-metal stents versus drug-eluting stents; 5 addressing CABG versus medical therapy; 1 addressing PCI versus medical therapy; and 1 addressing drug-eluting stents versus balloon angioplasty. Of 32 studies reporting information on variable selection, 7 relied exclusively on statistical criteria for the association of covariates with treatment, and 5 used such criteria to determine whether product or nonlinear terms should be included in the propensity score model. Twenty-five (52%) studies reported assessing covariate balance using the estimated propensity score, but only 1 described modifications to the propensity score model based on this assessment. The over 400 variables used in the 48 propensity score models were classified into 12 categories and 60 subcategories; only 17 subcategories were represented in at least half of the propensity score models. Overall, reporting of propensity score-based methods in observational studies comparing CABG, PCI, and medical therapy was incomplete; when adequately described, the methods used were often inconsistent with current methodological standards.

Effectiveness of Tympanostomy Tubes for Otitis Media: A Meta-analysis.

CONTEXT: Tympanostomy tube placement is the most common ambulatory surgery performed on children in the United States. OBJECTIVES: The goal of this study was to synthesize evidence for the effectiveness of tympanostomy tubes in children with chronic otitis media with effusion and recurrent acute otitis media. DATA SOURCES: Searches were conducted in Medline, the Cochrane Central Trials Registry and Cochrane Database of Systematic Reviews, Embase, and the Cumulative Index to Nursing and Allied Health Literature. STUDY SELECTION: Abstracts and full-text articles were independently screened by 2 investigators. DATA EXTRACTION: A total of 147 articles were included. When feasible, random effects network meta-analyses were performed. RESULTS: Children with chronic otitis media with effusion treated with tympanostomy tubes compared with watchful waiting had a net decrease in mean hearing threshold of 9.1 dB (95% credible interval: -14.0 to -3.4) at 1 to 3 months and 0.0 (95% credible interval: -4.0 to 3.4) by 12 to 24 months. Children with recurrent acute otitis media may have fewer episodes after placement of tympanostomy tubes. Associated adverse events are poorly defined and reported. LIMITATIONS: Sparse evidence is available, applicable only to otherwise healthy children. CONCLUSIONS: Tympanostomy tubes improve hearing at 1 to 3 months compared with watchful waiting, with no evidence of benefit by 12 to 24 months. Children with recurrent acute otitis media may have fewer episodes after tympanostomy tube placement, but the evidence base is severely limited. The benefits of tympanostomy tubes must be weighed against a variety of associated adverse events.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

OBJECTIVES: To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). STUDY DESIGN AND SETTING: We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. RESULTS: We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. CONCLUSION: The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters.

Oral Mechanical Bowel Preparation for Colorectal Surgery: Systematic Review and Meta-Analysis.

BACKGROUND: Oral mechanical bowel preparation is often used before elective colorectal surgery to reduce postoperative complications. OBJECTIVE: The purpose of this study was to synthesize the evidence on the comparative effectiveness and safety of oral mechanical bowel preparation versus no preparation or enema. DATA SOURCES: We searched MEDLINE, the Cochrane Central Register of Controlled Trials, Embase, and CINAHL without any language restrictions (last search on September 6, 2013). We also searched the US Food and Drug Administration Web site and ClinicalTrials.gov and supplemented our searches by asking technical experts and perusing reference lists. STUDY SELECTION: We included English-language, full-text reports of randomized clinical trials and nonrandomized comparative studies of patients undergoing elective colon or rectal surgery. For adverse events we also included single-group cohort studies of at least 200 participants. INTERVENTIONS: Interventions included oral mechanical bowel preparation, oral mechanical bowel preparation plus enema, enema only, and no oral mechanical bowel preparation or enema. MAIN OUTCOME MEASURES: Anastomotic leakage, all-cause mortality, wound infection, peritonitis/intra-abdominal abscess, reoperation, surgical site infection, quality of life, length of stay, and adverse events were measured. We synthesized results across studies qualitatively and with Bayesian random-effects meta-analyses. RESULTS: A total of 18 randomized clinical trials, 7 nonrandomized comparative studies, and 6 single-group cohorts were included. In meta-analyses of randomized clinical trials, the credibility intervals of the summary OR included the null value of 1.0 for comparisons of oral mechanical bowel preparation and either no oral preparation or enema for overall mortality, anastomotic leakage, wound infection, peritonitis, surgical site infection, and reoperation. These results were robust to extensive sensitivity analyses. Evidence on adverse events was sparse. LIMITATIONS: The study was limited by weaknesses in the underlying evidence, such as incomplete reporting of relevant information, exclusion of non-English and relevant unpublished studies, and possible missed indexing of nonrandomized studies. CONCLUSIONS: Our results could not exclude modest beneficial or harmful effects of oral mechanical bowel preparation compared with no preparation or enema.

Cranial radiation for pediatric T-lineage acute lymphoblastic leukemia: a systematic review and meta-analysis.

There are heterogeneous approaches to cranial radiation therapy (CRT) for T-lineage acute lymphoblastic leukemia (T-ALL). We performed a systematic review of studies that specified a radiation strategy and reported survival for pediatric T-ALL. Our analysis included 62 publications reporting 78 treatment groups (patient n = 5844). The average event-free survival (EFS) was higher by 6% per 5 years (P < 0.001). Adjusting for year, EFS differed by radiation strategy. Compared to the reference group (CRT for all) which had a year-adjusted EFS of 65% (95% confidence interval, CI: 61-69%) the adjusted EFS was significantly worse (rate difference (RD) = -9%, 95% CI: -15 to -2%) among studies that used a risk-directed approach to CRT (P = 0.004). The adjusted EFS for the other strategies were not significantly different compared to the reference group: CRT for central nervous system positive patients only (RD = -3%, 95% CI: -14 to 7%, P = 0.49); CRT omitted for all patients (RD = 5%, 95% CI: -4 to 15%, P = 0.33). CRT may not be necessary with current chemotherapy for T-ALL. These findings, however, are susceptible to bias and caution should be applied in drawing conclusions on the comparative effectiveness of alternative CRT strategies.

Genotype misclassification in genetic association studies of the rs1042522 TP53 (Arg72Pro) polymorphism: a systematic review of studies of breast, lung, colorectal, ovarian, and endometrial cancer.

Preferential loss of heterozygosity at the rs1042522 locus of the tumor protein 53 gene (TP53) (Arg72Pro) is observed in several tumors. Genetic association studies in oncology often use tumor tissue rather than unaffected tissue for genotyping; in such cases, loss of heterozygosity at the TP53 locus could lead to differential misclassification and could bias estimates of association. We searched multiple databases (through March 8, 2011) for studies investigating the association of Arg72Pro with breast, lung, colorectal, ovarian, or endometrial cancer. Meta-analysis was performed with multilevel Bayesian models. Informative priors for the bias effect were derived from a meta-analysis of the same polymorphism in cervical cancer. Of 160 studies (68 breast, 42 lung, 26 colorectal, 16 ovarian, and 8 endometrial cancer), 22 used tumor tissue as the source of genotyping material for cases. Use of tumor tissue versus other sources of genotyping material was associated with an apparent protective effect of the proline allele (relative odds ratio = 0.78, 95% credible interval: 0.70, 0.88). The probability that use of tumor tissue induced bias was estimated to be higher than 99%. Use of tumor tissue as the source of genotyping material for cases is associated with significant bias in the estimate of the genetic effect in cancer genetic association studies.